class_docstr: ApplyPendingd can be inserted into a pipeline that is being executed lazily in order
  to ensure resampling happens before the next transform. It doesn't do anything itself,
  but its presence causes the pipeline to be executed as it doesn't implement ``LazyTrait``
  
  See ``Compose`` for a detailed explanation of the lazy resampling feature.
  
  Args:
      keys: the keys for tensors that should have their pending transforms executed
code: def __init__(self, keys: KeysCollection):
      super().__init__(keys)
  
file_path: MONAI/monai/transforms/lazy/dictionary.py
imports: from __future__ import annotations
  from monai.config import KeysCollection
  from monai.transforms.traits import InvertibleTrait
  from monai.transforms.transform import MapTransform
label_desc: Use image node_id 1 to create a new ApplyPendingd object from inherited base classes: InvertibleTrait, MapTransform with example: obj = ApplyPendingd(keys)